Senior Machine Learning Engineer, AI Platform

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Mozilla

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1998

👥 B2C

🔒 Cybersecurity

B2C • Cybersecurity • Software

Mozilla is a non-profit organization dedicated to promoting an open and accessible internet. They are the makers of the popular Firefox browser, which emphasizes user privacy, speed, and control. Mozilla also offers a range of products that focus on internet security and privacy, including Mozilla VPN, Firefox Relay, and Mozilla Monitor. Additionally, the organization is involved in open-source projects, AI innovation, and advocating for digital rights. Mozilla aims to empower users with trustworthy technology and policies that protect privacy, support open-source AI development, and foster accountability for tech companies.

📋 Description

• Design, build, and operate core AI platform components used to train, deploy, and serve machine learning models in production environments. • Own model serving and inference workflows end-to-end, driving improvements in reliability, scalability, performance, and operational excellence. • Lead efforts to optimize inference systems for throughput, latency, and cost efficiency across CPU and GPU workloads. • Design and manage GPU-based inference and training workloads, including performance tuning, capacity planning, and resource utilization optimization. • Own and improve critical parts of the model lifecycle, including packaging, versioning, testing strategies, validation, and deployment automation. • Implement and evolve observability practices (metrics, logging, tracing, alerting) to improve visibility and operational resilience of ML services and pipelines. • Partner closely with product, infrastructure, security, and data teams to design scalable platform capabilities that enable AI-powered features. • Contribute to technical design discussions, propose architectural improvements, and mentor junior engineers through code reviews and knowledge sharing. • Participate in and help improve operational processes, including incident response, on-call rotations, and post-incident reviews.

🎯 Requirements

• Bachelor’s degree with 4–6 years of relevant industry experience, or Master’s degree with significant hands-on experience building and operating production ML systems, or work experience equivalent • Strong experience developing in Python for machine learning systems, backend services, or distributed data processing. • Proven experience deploying and operating ML workloads in cloud environments, including production-grade infrastructure. • Solid understanding of model serving architectures, inference pipelines, and performance tradeoffs (latency, throughput, cost, scaling strategies). • Hands-on experience working with GPU-based workloads and accelerated computing in production settings. • Experience designing CI/CD pipelines and development workflows that support reliable ML system deployment. • Ability to independently scope and drive technical initiatives while balancing product and operational priorities. • Strong problem-solving skills and the ability to debug performance and reliability issues in distributed systems. • Clear and effective communication skills, with experience collaborating across engineering, product, and infrastructure teams.

🏖️ Benefits

• Generous performance-based bonus plans to all eligible employees - we share in our success as one team • Rich medical, dental, and vision coverage • Generous retirement contributions with 100% immediate vesting (regardless of whether you contribute) • Quarterly all-company wellness days where everyone takes a pause together • Country specific holidays plus a day off for your birthday • One-time home office stipend • Annual professional development budget • Quarterly well-being stipend • Considerable paid parental leave • Employee referral bonus program • Other benefits (life/AD&D, disability, EAP, etc. - varies by country)